Biomimemic Opportunistic Approaches in Energy-Conserving/Harvesting Flight-Path Modeling for UAS

This paper presents two methods for planning the trajectories of fixed wing MAV or UAV through a meso−γ sized wind-field such that the energy in the atmospheric convection can be extracted to extend range and endurance. One of the methods utilizes potential flow theory to transform the state of energy in the wind field into a collection of sources and sinks, which it then uses to plan a trajectory that predominantly favors regions of updraft. The second method identifies multiple locales of high updraft in the wind-field, which it converts into vertices and edges, along which the cost of traversing is evaluated and treated as edge weight. This allows the best trajectory through the wind-field to be planned using a modified Bellman-Ford algorithm. The two approaches are compared to a baseline trajectory, which ignores the presence of the wind-field. This is accomplished through the flight simulation of a hypothetical 250 kg piston-propeller powered UAV.  It is shown that substantial improvement in fuel economy is to be expected in topography of strong mechanical convection.